Natural Language Processing: Application areas within NLP include automatic (machine) translation between languages; dialogue systems, which allow a human to interact with a machine using natural language; and information extraction, where the goal is to transform unstructured text into structured (database) representations that can be searched and browsed in flexible ways…

Machine Learning: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Neural Networks for Machine Learning: Learn about artificial neural networks and how they’re being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We’ll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

‘Probabilistic Graphical Models‘: In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

Computing for Data Analysis: This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.